Realistic modeling for facial animation
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Reading between the lines—a method for extracting dynamic 3D with texture
VRST '97 Proceedings of the ACM symposium on Virtual reality software and technology
From Multiple Stereo Views to Multiple 3-D Surfaces
International Journal of Computer Vision
An anthropometric face model using variational techniques
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Synthesizing realistic facial expressions from photographs
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Head shop: generating animated head models with anatomical structure
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Automatic Creation of 3D Facial Models
IEEE Computer Graphics and Applications
SIGGRAPH '81 Proceedings of the 8th annual conference on Computer graphics and interactive techniques
Modeling and animating for the dense laser-scanned face in the low resolution level
MS'06 Proceedings of the 17th IASTED international conference on Modelling and simulation
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This paper presents a new efficient method for the reconstruction of a personalized 3D facial model for animation from range data. Our method adapts a generic control model with anatomical structure to the geometry of a specific person's face with minimum manual intervention. The face adaptation algorithm starts with the specification of a small set of anthropometric landmarks on the 2D images of both the generic control model and individual face. 3D positions of landmarks are recovered automatically by using a projection-mapping approach. A global adaptation is then carried out to adapt the size, position and orientation of the generic model in the 3D space based on a series of measurements between the recovered 3D landmarks. After the global adaptation, a local adaptation deforms the generic model to fit all of its vertices to the scan data-set. The underlying muscle structure is automatically adapted as well, such that the reconstructed model not only resembles the individual face in shape and color but also reflects the structure of human face including skin and muscles, therefore can be animated immediately with the given muscle parameters.